WO2019154371A1

WO2019154371A1 - Scheduling method and system

Info

Publication number: WO2019154371A1
Application number: PCT/CN2019/074602
Authority: WO
Inventors: 李锐; 高为静; 孙淑娟
Original assignee: 中兴通讯股份有限公司
Priority date: 2018-02-09
Filing date: 2019-02-02
Publication date: 2019-08-15
Also published as: CN110139289B; CN110139289A

Abstract

Disclosed in the present application are a scheduling method and system for a communication system. The method comprises: monitoring a network state of a network within a current coverage area in real time; in response to determining that a key network index in the network state is within a preset threshold range, generating a new network model parameter according to an obtained network policy and an optimization parameter; and re-configuring the network according to the new network model parameter.

Description

Scheduling method and scheduling system

The present application claims priority to Chinese Patent Application No. 201101132133, filed on Jan.

Technical field

The present application relates to, but is not limited to, a wireless communication system, such as a scheduling method and scheduling system of a communication system.

Background technique

The related wireless communication systems are mostly Cellular Mobile Communication systems, which adopt a cellular wireless networking mode, and are connected through a wireless channel between the terminal and the network device, thereby enabling users to communicate with each other during activities. The main feature of wireless communication is the mobility of the terminal, and it has the function of handoff and automatic roaming across the local network.

The wireless communication splits the covered area into different cells, and provides services such as voice, data, and video images through different frequency points and complex network topologies. With the development of several generations of technology, the current wireless cellular communication is very mature.

The Radio Access Network (RAN) is a very important part of wireless communication. While the RAN's improvement scheme focuses on gradually improving the coverage and user experience of the network, it also makes the network topology and inter-cell coordination of the cell more and more complicated. In order to further improve the network performance, the stations of the radio access network are deployed more and more densely, the cells are split smaller and smaller, and the energy consumption and management are more and more complicated. The high-low frequency hybrid networking in the 5th Generation (5G) communication system will also face such a situation.

At present, the design of the RAN is relatively closed, and the overall architecture is aimed at providing coverage and performance, and is insensitive to network perception and not intelligent enough. Although 5G introduced some cloud ideas in Internet Technology (IT), it hopes to avoid the tidal effect of communication. However, due to the architecture design and deployment cost of the entire network, it cannot be deployed on a large scale. .

Summary of the invention

The following is an overview of the topics detailed in this document. This summary is not intended to limit the scope of the claims.

The present application provides a scheduling method and a scheduling system, which can flexibly and automatically implement control of a communication system while ensuring normal use of the network by users.

The present application provides a scheduling method, including: real-time monitoring of a network state of a network in a current coverage domain; and responding to determining that a critical network indicator in a network state is within a preset threshold range, generating a new one according to the obtained network policy and optimization parameters. Network model parameters; reconfigure the network within the current coverage domain based on the new network model parameters.

The application further provides a computer readable storage medium storing computer executable instructions arranged to perform the scheduling method of any of the above.

The present application further provides a scheduling apparatus, including a processor, a memory, and a computer program stored on the memory and operable on the processor: real-time monitoring of a network state of a network in a current coverage domain; and responding to determining a key network indicator in a network state Within the preset threshold range, new network model parameters are generated according to the obtained network policy and optimization parameters; the network in the current coverage domain is reconfigured according to the new network model parameters.

The application further provides a scheduling system, comprising: an information processing unit, a service operation unit, and a policy unit; wherein the information processing unit is configured to collect network status of the network in the current coverage domain, in response to determining a critical network in the network status The indicator generates a new network model parameter according to the network policy and the optimization parameter from the policy unit within a preset threshold range; the service operation unit is configured to reconfigure the network in the current coverage domain according to the new network model parameter; the policy unit, setting Interact network policies and optimize parameters with the service management network element.

Other aspects will be apparent upon reading and understanding the drawings and detailed description.

DRAWINGS

The drawings are used to provide a further understanding of the technical solutions of the present application, and constitute a part of the specification, which is used together with the embodiments of the present application to explain the technical solutions of the present application, and does not constitute a limitation of the technical solutions of the present application.

1 is a schematic diagram of a wireless network networking mode in the related art;

2 is a schematic diagram of a first embodiment of implementing network coverage according to different deployment scenarios of the network according to the present application;

3 is a schematic diagram of a second embodiment of implementing network coverage according to different deployment scenarios of the network according to the present application;

4 is a schematic diagram of a first embodiment of a scheduling system of the present application in a network;

5 is a schematic diagram of a second embodiment of a scheduling system of the present application in a network;

6 is a schematic structural diagram of a scheduling system of the present application;

FIG. 7 is a schematic flowchart diagram of a method for implementing control in a scheduling system of the present application.

Detailed ways

Embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that, in the case of no conflict, the features in the embodiments and the embodiments in the present application may be arbitrarily combined with each other.

With the development of technology, related technology networks need to further enhance network perception and corresponding intelligent design. For example, the processing of energy consumption, FIG. 1 is a schematic diagram of a wireless network networking mode in the related art. As shown in FIG. 1 , no matter how the users in the coverage cell are distributed, once the network planning is completed, the radio remote unit (RRU) ) / Active Antenna Units (AAU) and Baseband Units (BBUs) will remain active at all times, which undoubtedly wastes resources. For some special scenes such as subways, shopping malls, etc., in order to reduce the waste of resources, the staff will power off the communication system when the subway stops operating or the mall is snoring, and then power on when the subway operates or the mall is open. However, on the one hand, the control of the communication system relies on manual intervention, and the scalability is poor. On the other hand, the communication system is not only a commercial network, but also a social infrastructure. This discontinuity of network coverage caused by power failure affects User's normal use during this time period.

Compared with the traditional manual intervention, the applicant proposes that if the communication system can identify different application scenarios, for some cells with fewer users, users in these cells are first moved into a cell, which may be a new cell. Hereinafter, it is called a merged cell; after that, the capacity and power of the merged cell are increased to keep the coverage area unchanged; then, those inactive cells with fewer users are closed, and the network topology is optimized, so that energy saving can be achieved. It also guarantees good coverage. When the user or traffic of the merged cell is active to a certain extent, the network plan of the initial configuration of the system is restored. In this way, coverage capacity and energy-saving automation adjustments can be achieved. As shown in FIG. 2 or FIG. 3, the example shown in FIG. 2 shows that it is assumed that seven cells (such as the hexagon shown by the dotted line in FIG. 2) can be combined into one cell according to the current network state (see FIG. 2). The hexagon shown in the figure is implemented; the example shown in Figure 3 shows that it is assumed that according to the current network state, 7 cells (such as the hexagon shown by the dotted line in Fig. 3) can be merged into 3 cells (Fig. 3). Three-part cell represented by different shades). That is to say, through FIG. 2 or FIG. 3, a corresponding coverage solution can be adopted according to different deployment scenarios of the network.

In order to implement the above process, the present application adds a scheduling system to the radio access network. The scheduling system of the present application can be set in the network as shown in FIG. 4 or FIG. 5. Figure 4 shows a scenario in which a centralized unit (CU) and a distributed unit (DU) of a BBU function are deployed in a 4G/5G network. The new scheduling system can manage multiple BBUs. Figure 5 shows the scenario where the CU and the DU of the BBU function are deployed separately in the 4G/5G network. The new scheduling system can manage multiple CUs and multiple DUs.

The scheduling system is configured to monitor the running state of the wireless network and the user behavior of the network, and when the network state and the user behavior change and reach a preset threshold, the preset template (ie, a series of parameters are arranged in a specified format). The collection parameter or the network's self-calculating optimization parameters (which may be parameters within the template or other parameters), automatically reconfigure the network, enabling the network to adapt to the state of the current network, to achieve self-optimization of coverage and scheduling, and intelligence Energy saving.

In an embodiment, the network operating state includes, but is not limited to, at least one of the following: a current radio access network carrier frequency band, a network capacity, a user location, a number of user connections, a number of user activations, user traffic, and radio frequency power.

In an embodiment, the user behavior includes but is not limited to at least one of the following: a current running state of the user, such as an active state or an inactive state, a user service attribute such as real-time or non-real-time, and a user traffic such as a large traffic or a small traffic. And user business behavior such as voice or web browsing.

In an embodiment, the preset threshold is a set of indicators based on network running status and user behavior, and the indicator may be a template threshold that is pre-imported by the user (that is, a set of parameter thresholds arranged in a specified format), or may be The model threshold (the parameter threshold of the template and the threshold of the optimization parameter) obtained by the scheduling system through big data training or machine learning. The big data training or the machine learning may include: performing data mining or feature extraction on a large amount of data collected by the collected network, and performing the iterative calculation on the extracted feature data feedback, and calculating an optimal model value as a model threshold.

In an embodiment, the network self-calculating optimization parameters include: physical-layer cell identity (PCI) reselection, carrier frequency band selection, radio frequency power adjustment, and radio channel selection. The PCI reselection of the merged cell may be reselected from several cells before the merge, or selected from the planned PCI pool.

FIG. 6 is a schematic structural diagram of a scheduling system of the present application. As shown in FIG. 6, the method includes at least an information processing unit, a service operation unit, and a policy unit.

The information processing unit is configured to collect network status of the network in the current coverage area, and generate new information according to the network policy from the policy unit and the optimization parameter calculated by the network in response to determining that the critical network indicator in the network status is within a preset threshold range. Network model parameters.

The business operations unit is configured to reconfigure the network within the current coverage domain based on the new network model parameters.

The policy unit is set to be responsible for interacting with the Element Management System (EMS) to exchange network policies and optimize parameters.

In an embodiment, a log unit is further included, configured to record an operation result of the service operation unit.

In an embodiment, the network status includes network operating status, user behavior, and the like.

In an embodiment, the critical network indicator is a pre-specified number of users in the coverage domain, network load, and the like. For example, for a single site coverage scenario, the key network indicators may include, but are not limited to, network traffic or number of network users in the cell; for example, for subway and mall coverage scenarios, key network indicators may include, but are not limited to, network traffic or intra-cell The number of network users; for example, for high-frequency and low-frequency hybrid networking scenarios, the key network indicators may include, but are not limited to, the number of network users and traffic in the high-frequency hotspot cell; for example, for the 4G and 5G hybrid networking scenarios, the critical network The indicators may include, but are not limited to, the number of user network users and traffic in the 5G hotspot cell.

It should be noted that multiple component units of the scheduling system may be disposed on the same entity or may be grouped on different entities.

In an embodiment, the log unit is further configured to report the log record of the current operation to the EMS.

In an embodiment, the policy unit is further configured to: report the current network status information to the EMS. In this way, the EMS can analyze the current network status in the background. If the adjustment result of adjusting the network structure by using the EMS itself to generate a new network model parameter is better than the network structure adjustment result reported by the scheduling system, the EMS will generate a new one according to the EMS itself. The network model parameters update the network policy so that the policy log unit subsequently obtains a better network policy. Here, the EMS can directly send the updated network policy to the policy log unit, or store the updated network policy, and wait for the policy log unit to interact with the EMS.

In an embodiment, the information processing unit includes: a service detection module, a service analysis module, a model processing module, and an information storage module.

The service detection module is configured to monitor in advance real-time specified key network indicators such as the number of users and network load in the current coverage area.

The service analysis module is configured to analyze key network indicators, such as network load and user model, according to network status information, and respond to key network indicators within a preset threshold range, such as the entire network load or the number of network users in some cells. Decreasing or rising to a preset threshold range, analyzing and predicting possible network behavior of the network according to historical information and historical parameters stored in the current coverage domain in the information storage module, and requesting a new network from the model processing module The configuration strategy may include: analyzing, by using information about the currently monitored network status, whether the change of the number of users, the flow, and the like in some time periods is close to the historical information and parameters recorded in a certain period of time, if relatively close If the difference is within a certain preset range, it can be predicted that the next network behavior of the network is similar to that of the previous historical network. For example, most of the shopping malls will be drastically reduced after a certain period of time is closed. Consider merging some cells to save resources.

The model processing module is configured to calculate a new network model parameter according to the network policy from the policy unit and the optimized parameter calculated by the network, and report the new network model parameter to the policy unit, and notify the service operation unit of the obtained new network model parameter; The network model is configured with static parameters in advance. The calculation is based on the specific operational state of the network to optimize the parameters that can be optimized, so as to obtain new network model parameters and report the data.

The information storage module is configured to store the network configuration information from the service operation unit that needs to be adjusted and the user before adjustment, such as user data that needs to be migrated.

In an embodiment, the service operation unit includes at least one of the following modules: a resource operation module, a radio frequency baseband operation module, and a cell operation module.

The resource operation module is configured to allocate or recycle a computing resource, a storage resource, or a network resource of the radio access network for the cell and the user that needs to be adjusted according to the new network model parameter from the information processing unit, or open according to the resource requirement Or close the board or chassis.

The radio frequency baseband operation module is configured to adjust the radio frequency unit and the baseband processing unit, such as turning off or turning on certain carrier frequency points and radio frequency channels, according to the new network model parameters from the information processing unit, for the cells and users that need to be adjusted.

The cell operation module, according to the new network model parameter from the information processing unit, merges multiple cells or splits at least one cell for the cell and user to be adjusted, and migrates the user in the current coverage area to the new network model parameter. In the planned cell, the network configuration information before the adjustment of the cell and the user to be adjusted is stored in the information storage module of the information processing unit.

In the present application, after the service operation unit adjusts the network, such as cell merge or split, according to the new network model parameters calculated by the information processing unit, in order to minimize the influence of the original user's service usage, the service operation unit saves the network adjustment before The network configuration information (such as the cache information of the access network) in the information storage module is restored, so that even if the network is adjusted, the user may not perceive the network change.

It can be seen that the service operation unit can operate on a single base station (eNB or gNB) according to the currently calculated new network model parameters, such as turning off or turning on different carrier frequency points and radio frequency channels of a single base station; Cooperative operations between base stations, such as cell merging, re-adjusting the wireless resources of the system.

In an embodiment, the policy unit includes: a policy synchronization module and a key performance indicator module.

The policy synchronization module is configured to receive the network policy from the EMS and the optimized parameters that are calculated by the network and output the information to the information processing unit. In an embodiment, the policy synchronization module is further configured to: report the current network status information to the EMS. .

The key performance indicator module is configured to obtain key performance indicators of the current network from the service detection module in the information processing unit.

In an embodiment, the preset threshold is a set of indicators based on network running status and user behavior; the threshold is a template threshold that is pre-introduced by the user; or the threshold is a model threshold obtained by big data training or machine learning, and the optimized parameter is Number threshold.

In an embodiment, when the threshold is a model threshold obtained by big data training or machine learning and a threshold of the optimization parameter, the service analysis module in the information processing unit is further configured to:

Perform big data training and machine learning on the collected data. For example, through data mining or feature extraction, the extracted feature data feedback is iteratively calculated, and the optimal model coefficients are calculated; the learned network model threshold and the threshold of the optimized parameters are learned. The feedback is sent to the policy unit for further manual optimization processing; and the learned network model threshold and the threshold of the optimization parameter are output to the business operation unit for use.

By adding the scheduling system of the present application in the network, if the user behavior or the network environment, such as, but not limited to, the number of important network indicators such as the number of users and network traffic changes, the network automatically changes and the current wireless access network is migrated to the network. The initial state (that is, the network mode planned according to the typical application scenario, the typical scenario configures the network according to the maximum demand) or another planning model state, flexibly and automatically realizes the intelligent control of the communication system, and ensures the user to the network. Normal use.

The user adds the scheduling system to the relevant wireless access network, and configures a corresponding scheduling system for the specified wireless coverage area. Based on the relevant radio access network planning and deployment, and corresponding parameters and models, the user formulates multiple coverage strategies, and presets some adjustable parameters to the system for adjustment based on each coverage strategy.

The implementation control of the scheduling system of the present application is described in detail below in conjunction with specific application scenarios.

The first implementation use case is exemplified by a single site coverage optimization.

It is assumed that the user adds a scheduling system to the relevant radio access network, and a corresponding scheduling system is configured for the site of the specified radio coverage area. Moreover, according to the relevant radio access network planning and deployment, and the corresponding parameters and models, the user separately formulates two coverage strategies, namely the working time period and the non-working time period, namely the network strategy in the above, and the basis of multiple coverage strategies. The reserved parameters are adjustable optimization parameters such as carrier frequency, RF channel, RF power, etc. to be adjusted by the system. As can be seen in conjunction with Figure 6,

The service detection module monitors important network indicators such as the number of users and network load in the current coverage area in real time; after obtaining the monitoring information, the service analysis module analyzes key network indicators such as network load and user model, if network traffic or number of network users in the cell Falling into the preset threshold range, that is, entering the processing mode of the non-working time period, analyzing and predicting the possible network behavior of the network according to the historical information and configuration of the network in the current coverage domain, and requesting the new network configuration strategy from the model processing module. The model analysis module calculates new network model parameters and reports them to the policy unit according to the network policy from the policy unit and the optimized parameters calculated by the network, and informs the service operation unit to perform corresponding processing and needs to adjust the cells. And the user's information is stored in the information storage module.

The business operation unit adjusts new network parameters and configurations according to the new network model parameters, and records the operation results in the log unit. The resource operation module allocates or reclaims resources such as computing resources, storage resources, or network resources of the radio access network; or enables or disables some boards or chassis according to resource requirements. If some sites are configured with multiple carriers, the RF baseband operation module will turn off part of the carrier and RF channels to reduce system power consumption; and the cell operation module will merge multiple cells in the coverage area, and the cells and users that need to be adjusted are The network configuration information before the adjustment is the cell merging. The network configuration information needs to be adjusted and stored in the information storage module. After the network information is adjusted, the service operation unit uses the cell and user information stored in the information storage module to restore the user data.

The policy synchronization module outputs the received network policy from the EMS and the optimized parameters obtained by the network to the information processing unit, and reports the current network status information to the EMS. The log records of the current operation are stored and reported to the EMS.

In this way, the number of users and network traffic begin to change during the working period. If the preset threshold is exceeded, the network will automatically change, multiple cells are powered on, and the macro cell is divided into multiple micro cells. The system will be radio frequency and baseband. Network parameters such as cells are migrated to the default working state of the network system itself.

The second implementation use case takes the subway and shopping mall coverage scene as an example.

It is assumed that the user adds a scheduling system to the relevant wireless access network, and configures a corresponding scheduling system for the designated wireless coverage area, that is, the subway or the shopping mall. Moreover, according to the relevant radio access network planning and deployment, and the corresponding parameters and models, the user separately formulates two coverage strategies, namely the working time period and the non-working time period, namely the network strategy in the above, and the basis of multiple coverage strategies. The reserved parameters are adjustable optimization parameters such as carrier frequency, RF channel, RF power, etc. to be adjusted by the system. As can be seen in conjunction with Figure 6,

The business operation unit adjusts new network parameters and configurations according to the new network model parameters, and records the operation results in the log unit. The resource operation module allocates or reclaims resources such as computing resources, storage resources, or network resources of the radio access network; or enables or disables some boards or chassis according to resource requirements. The RF baseband operation module will turn off part of the baseband processing unit to increase the power of the radio unit to increase the coverage area; and the cell operation module will merge multiple cells in the coverage area, and the network configuration information of the cell and the user to be adjusted before adjustment That is, the cell is merged, and the previous network configuration information needs to be adjusted and stored in the information storage module. After the network information is adjusted, the service operation unit uses the cell and user information stored in the information storage module to restore the user data.

The business analysis module in the information processing unit performs big data training and machine learning on the collected data, such as data mining or feature extraction, and the extracted feature data is fed back to the iterative calculation to calculate the optimal model coefficient; The network model threshold and the threshold of the optimization parameter are fed back to the policy unit for further manual optimization processing; and the learned network model threshold and the threshold of the optimization parameter are output to the service operation unit for use.

The third implementation example takes a high frequency and low frequency hybrid networking scenario as an example.

It is assumed that the user adds a scheduling system to the relevant radio access network, and a corresponding scheduling system is configured for the site of the specified radio coverage area. Moreover, according to the planning and deployment of the relevant radio access network, and the corresponding parameters and models, the user respectively formulates a coverage strategy for the low-band macro cell to solve the coverage strategy and the high-band micro-cell to absorb the hotspot capacity, that is, the network strategy above. On the basis of multiple coverage strategies, some parameters are reserved for adjustable optimization parameters such as carrier frequency, radio frequency channel, radio frequency power, capacity, etc. to be adjusted by the system.

As shown in FIG. 6, the service detection module monitors the number of users in the current coverage area, network load and other important network indicator information in real time; after obtaining the monitoring information, the service analysis module analyzes key network indicators such as network load and user model, if high frequency The number of network users and traffic in the hotspot cell falls within a preset threshold range. According to the historical information and configuration of the network in the current coverage domain, the next possible network behavior of the predicted network is analyzed, and a new network configuration policy is requested from the model processing module. The model analysis module calculates new network model parameters and reports them to the policy unit according to the network policy and optimization from the policy unit. For example, under the current network condition, the high frequency hotspot cell can be turned off, and the low frequency cell needs to be added. The capacity is covered, and the service operation unit is informed to perform corresponding processing and the information of the high frequency hotspot cell and the user that needs to be adjusted is stored in the information storage module.

The business operation unit adjusts new network parameters and configurations according to the new network model parameters, and records the operation results in the log unit. The resource operation module closes the site of the high frequency hotspot cell and increases the resource allocation of the low frequency cell; the RF baseband operation module turns off the high frequency cell site, increases the RF power of the low frequency station, and increases the coverage area; and the cell operation module merges Multiple cells in the area are covered, and the high-frequency hotspot cell and the user are merged in the network configuration information before the adjustment, that is, the network configuration information needs to be adjusted and stored in the information storage module. After the network information is adjusted, the service operation unit The user data is restored by using the cell and user information stored in the information storage module.

The policy synchronization module outputs the received network policy from the EMS and the optimized parameters calculated by the network to the information processing unit, and reports the current network status information to the EMS. The log records of the current operation are stored and reported to the EMS.

In this way, as the number of users increases, the number of connections and network traffic begin to change. After the above-mentioned preset threshold is exceeded, the network is automatically changed, the high-frequency hotspot cell is dispersed, and the low-frequency cell power is kept to maintain a certain coverage area. The radio frequency, baseband, and The network parameters such as the cell are migrated to the default working state of the network system itself.

The fourth implementation example takes a 4G and 5G hybrid networking scenario as an example.

It is assumed that the user adds a scheduling system to the relevant radio access network, and a corresponding scheduling system is configured for the site of the specified radio coverage area. Moreover, the user separately formulates a 4G macro cell solution coverage strategy according to the relevant radio access network planning and deployment, and corresponding parameters and models, and the coverage strategy of the 5G micro cell absorbing hotspot capacity is the above network policy, and multiple On the basis of the coverage strategy, some parameters are reserved for adjustable optimization parameters such as carrier frequency, radio frequency channel, radio frequency power, capacity, etc. to be adjusted by the system. As can be seen in conjunction with Figure 6,

The service detection module monitors the number of users in the current coverage area, network load and other important network indicator information in real time; after obtaining the monitoring information, the service analysis module analyzes key network indicators such as network load and user model, if the user network user in the 5G hotspot cell The number and traffic drop to a preset threshold range. According to the historical information and configuration of the network in the current coverage domain, the next possible network behavior of the predicted network is analyzed, and a new network configuration policy is requested from the model processing module; the model analysis module is Calculate the new network model parameters and report them to the policy unit according to the network policy from the policy unit and the optimized parameters obtained by the network. For example, under the current network conditions, the 5G hotspot cell can be shut down and the 4G cell needs to be added. The capacity is covered, and the service operation unit is informed to perform corresponding processing and the information of the high frequency hotspot cell and the user that needs to be adjusted is stored in the information storage module.

The business operation unit adjusts new network parameters and configurations according to the new network model parameters, and records the operation results in the log unit. The resource operation module will close the site of the 5G hotspot cell and increase the resource allocation of the 4G cell; the RF baseband operation module will close the 5G cell site, increase the RF power of the 4G site, and increase the coverage area; and the cell operation module will merge the coverage area. Multiple cells, and the 5G hotspot cell and the user before the adjustment of the network configuration information, that is, the cell merge, need to adjust the previous network configuration information, stored in the information storage module, after the network information is adjusted, the business operation unit reuse information The cell and user information stored in the storage module recovers user data.

In this way, as the number of users increases, the number of connections and network traffic begin to change. After the above-mentioned preset threshold is exceeded, the network automatically changes, the 5G hotspot cell is dispersed, and the 4G cell power is kept at a certain coverage area. The radio frequency, baseband, and cell are used. The network parameters are migrated to the default working state of the network system itself.

FIG. 7 is a schematic flowchart of a method for implementing control in a scheduling system according to the present application. As shown in FIG. 7, the method includes steps 700 to 702.

In step 700, the network status of the network within the current coverage area is monitored in real time.

Network status can include network health status and user behavior.

In an embodiment, user behavior includes, but is not limited to, at least one of: a user's current operational state (eg, active or inactive state), user traffic attributes (eg, real-time or non-real-time), user traffic (eg, Large or small traffic), as well as user business behavior (such as voice or web browsing).

In step 701, in response to determining that the key network indicator in the network state is within a preset threshold range, new network model parameters are generated according to the obtained network policy and optimization parameters.

In an embodiment, the critical network indicator is an important network indicator such as the number of users in the coverage domain and the network load. For example, for a single site coverage scenario, key network metrics may include, but are not limited to, network traffic or number of network users within the cell. For another example, for subway and shopping mall coverage scenarios, key network indicators may include, but are not limited to, network traffic or number of network users in the cell. For example, for a high frequency and low frequency hybrid networking scenario, the key network indicators may include, but are not limited to, the number of network users and the traffic in the high frequency hotspot cell. For example, for the 4G and 5G hybrid networking scenarios, the key network indicators may include, but are not limited to, the number of user network users and traffic in the 5G hotspot cell.

In an embodiment, the step includes: analyzing key network indicators, such as network load and user model, according to the monitored network status information, if the critical network indicator, such as the entire network load or the number of network users in some cells, is reduced or Rising to a preset threshold range, analyzing and predicting the possible network behavior of the network according to the historical information and parameters of the network in the current coverage domain stored in the information storage module, and according to the possible network behavior of the network, the model The processing module requests a new network configuration policy. The analysis may include: using information about the currently monitored network status, and analyzing whether the change of the number of users, the flow rate, and the like in some time periods is close to the historical information and parameters recorded in a certain period of time, if the difference is close to the difference Within a certain preset range, it can be predicted that the network behavior of the network is similar to that of the previous historical network. For example, the number of users in most shopping malls will be reduced after a certain period of time, and then the number of users may be considered to be merged. The cell saves resources.

The new network model parameters are calculated according to the requested network policy from the policy unit and the optimized parameters calculated by the network.

The network model is configured by pre-statically configuring parameters, and the calculation is to optimize the parameters that can be optimized according to the specific operational state of the network, thereby obtaining new network model parameters, and summarizing the data.

In step 702, the network within the current coverage domain is reconfigured according to the new network model parameters.

In an embodiment, this step may include at least one of the following.

According to the new network model parameters, for the cells and users that need to be adjusted: allocate or recycle the computing resources, storage resources, or network resources of the radio access network, or open or close the board or the chassis according to the resource requirements.

According to the new network model parameters, the radio unit and the baseband processing unit are adjusted for the cells and users that need to be adjusted, such as turning off/on certain carrier frequency points and radio frequency channels.

According to the new network model parameters, the cells and users that need to be adjusted are merged into multiple cells or split into at least one cell, and the users in the current coverage area are migrated to the newly planned cells in the new network model parameters.

The step further includes: storing the network configuration information before the adjustment of the cell and the user that needs to be adjusted.

The method of the present application further includes: reporting current network status information, such as a log and a key network indicator, and a log record of the current operation to the EMS.

In this way, the EMS can analyze the current network status in the background. If the adjustment result of adjusting the network structure by using the EMS itself to generate a new network model parameter is better than the network structure adjustment result reported by the scheduling system, the EMS will generate a new one according to the EMS itself. The network model parameters update the network policy so that the policy log unit subsequently obtains a better network policy. Here, the EMS can directly send the updated network policy to the policy log unit, or store the updated network policy, and wait for the policy log unit to interact with the EMS.

The embodiment of the present application further provides a computer readable storage medium storing computer executable instructions, the computer executable instructions being configured to perform the method for implementing control by the scheduling system according to any one of the above.

The embodiment of the present application further provides a scheduling apparatus, including a processor, a memory, and a computer program stored on the processor and operable on the processor: real-time monitoring a network state of a network in a current coverage domain; and responding to determining a critical network in a network state The indicator generates new network model parameters according to the obtained network policy and optimization parameters within a preset threshold range; and reconfigures the network in the current coverage domain according to the new network model parameters.

Claims

A scheduling method for a communication system, comprising:

Real-time monitoring of the network status of the network within the current coverage area;

Responding to determining that the key network indicator in the network state is within a preset threshold range, generating new network model parameters according to the obtained network policy and optimization parameters;

Reconfiguring the network based on the new network model parameters.
The scheduling method according to claim 1, further comprising: reporting the information of the network status and the log record of the operation of the reconfiguration network to the service management network element.
The scheduling method according to claim 1 or 2, wherein the responding to determining that the key network indicator in the network state is within a preset threshold range, generating new network model parameters according to the obtained network policy and optimization parameters ,include:

And analyzing, according to the information about the network status, the critical network indicator, analyzing, and predicting, according to the historical information and historical configuration of the network, that the critical network indicator is within the preset threshold range Possible next network behavior of the network;

Requesting a new network configuration policy according to possible network behavior of the network in the next step;

The new network model parameters are calculated according to the requested new network configuration policy and the optimized parameters calculated by the network.
The scheduling method according to claim 1, wherein the preset threshold is a set of indicators based on a network operating state and user behavior;

The preset threshold is a template threshold that is pre-introduced by the user; or the preset threshold is a model threshold obtained by big data training or machine learning and a threshold of the optimization parameter.
The scheduling method according to claim 1 or 2, wherein said reconfiguring said network according to new network model parameters comprises at least one of the following:

According to the new network model parameter, for the cell and the user that needs to be adjusted: allocate or recycle the computing resource, the storage resource or the network resource of the radio access network; or open or close the board or the chassis according to the resource requirement;

Adjusting the radio frequency unit and the baseband processing unit for the cell and the user that need to be adjusted according to the new network model parameter;

And combining, according to the new network model parameter, a plurality of the cells or splitting at least one of the cells for a cell and a user that needs to be adjusted, and migrating the user in the current coverage area to the new network model In the newly planned cell in the parameter.
A computer readable storage medium storing computer executable instructions, the computer executable instructions being arranged to perform the scheduling method of any one of claims 1 to 5.
A scheduling device for a communication system, comprising: a processor, a memory, and a computer program stored on the processor and operable on the processor: real-time monitoring of a network state of a network within the current coverage domain; and responsive to determining a critical network indicator in the network state Within the pre-set threshold range, new network model parameters are generated according to the obtained network policy and optimization parameters; the network is reconfigured according to the new network model parameters.
A scheduling system for a communication system, comprising: an information processing unit, a service operation unit, and a policy unit; wherein

The information processing unit is configured to collect a network status of a network in a current coverage area, and in response to determining that a critical network indicator in the network status is within a preset threshold range, calculate according to a network policy from the policy unit and the network The obtained optimization parameters generate new network model parameters;

The service operation unit is configured to reconfigure the network according to the new network model parameter;

The policy unit is configured to exchange network policies and optimization parameters with the service management network element.
The scheduling system according to claim 8, further comprising a log unit configured to record an operation result of said service operation unit.
The scheduling system according to claim 9, wherein the policy unit is further configured to: report the information about the network status to the service management network element;

The log unit is further configured to: report the log record of the operation of reconfiguring the network to the service management network element.
The scheduling system according to claim 8 or 9, wherein the preset threshold is a set of indicators based on network operating status and user behavior;

The preset threshold is a template threshold that is pre-introduced by the user; or

The preset threshold is a model threshold obtained by big data training or machine learning and a threshold of the optimization parameter.